Mary Jane Feigenbutz

Objective: Increase bot creation amongst first-time visitors

Approach: Upon analyzing existing customers’ bots, I created buckets of the most common bot use cases: Customer Care, Lead Generation, Shopping, and Content Discovery. I then collaborated with our content team to create standardized templates for each prominent use case in several languages.

Results: Pre-made templates were selected 5x more than original blank template. yielding a 30% higher activation rate.

Objective: Alleviate our customers' concerns regarding their end users’ experiences with the chatbot.

Approach: Create an interactive simulation of the bots workflow in a faux chat window for users to reference and test their bot flows as they were building. While chat previewers are now common in other Bot Building tools, Sprout’s release (as far as we know) was the first to market.

Results: Based on early qualitative feedback from users, this feature was quickly identified as one of the most critical for adoption and so was released with our first public MVP and was enhanced in every subsequent release, becoming a staple of the builder experience.

Objective: Help facilitate bot-building content collaboration within teams.

Approach: Upon learning through user interviews that several customers were taking screenshots of the bot builder workflow and/or video recordings of the interactive previewer to share with non Sprout Users, we developed the ability for users to generate secure URLs that directed recipients to a public landing page containing the bot workflow and previewer.

Results: This release marked the first solution of its kind to market, enabling users to share live, interactive data from within Sprout to an external landing page without requiring a user login, a concept applicable to so many other use cases that it resulted in the creation of an entire team dedicated to building out similar functionality for the entire application.

Objective: Help users understand the value of their chatbots and opportunities for improvement within their bot workflows.

Approach: Released Facebook & Twitter Bot Reports, allowing users to analyze their bots’ conversation volume, content performance , as well as inbound message trends leveraging a proprietary topic modeling algorithm to make bot interactions—as well as their broader social strategy— more effective.

Results: High weekly and monthly viewership of reports amongst customers with bots.

Objective: Allow users to configure automated bot responses for commonly received message words/phases.

Approach: Create a Keyword Builder to allow users to set rules surrounding specific keyword and phrase triggers and associated bot responses. For example, any time a bot receives a message that says "customer support," automatically send a message with information on how to contact customer support.

Results: This quickly became one of those most used feature within the Bot Builder suite and a key selling proposition.